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    <title>浏阳德塔软件开发有限公司 女娲计划</title>
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    <br/>第七章 类人DNA与神经元基于催化算子映射编码方式
    <br/>The Initons Catalytic Reflection Between Humanoid DNA and Nero
    Cell
    <br/>类人 DNA 与 神经元基于催化算子映射编码方式
    <br/>Yaoguang Luo, Rongwu Luo
    <br/>罗瑶光, 罗荣武
    <br/>Keywords
    <br/>VPCS, AOPM, IDUC, Nero, Artificial, Decoder, Medical, Paralling,
    Computing,
    <br/>Humanoid, ETL, Parser, Data Mining
    <br/>关键词
    <br/>VPCS 架构 AOPM 逻辑 IDUC 编码 神经元 人工 解码 医学 并行计算 类人仿生 ETL
    数据挖掘 爬取
    <br/>3. 2 Deta Catalytic computing development, 德塔催化计算发展
    <br/>R&D is not successful every time. In the process of butterfly
    calculation optimization of Fast Fourier, I coded the features of
    discrete DCT in complex numbers, which took me one month, but failed. I
    remembered that I said in Weibo at the beginning that I could speed up
    the calculation of Fast Fourier by 200 times, but I really didn't give
    up. Since butterfly calculation optimization was unsuccessful, I tried
    to sort the small peaks by fast left-right comparison. I was excited
    when I saw the 10th generation of single machine random double with a
    sorting speed of 12 million arrays per second of quick sorting. My
    thought is right, and thinning logic is an important way of human
    thinking. Here, the author designed an argumentation paper when
    designing fast word segmentation and extremely fast peak filtering
    catalytic sorting, as follows:
    <br/>
    研发并不是每一次都是成功的, 在快速傅里叶的蝶形运算优化过程中, 我将离散 DCT 的特征进行
    复数编码, 花了我 1 个月, 结果失败了, 想起刚开始时候我在微博里说我能将快速傅里叶计算速度
    加快 200 倍, 着实打了脸, 我并没有放弃, 既然蝶形计算优化不成功, 那么在快速左右比对小
    高峰过滤排序上试试? 当我看到单机随机 double 每秒1200 万数组排序速度的第 10 代及快速
    排序出来的时候, 我振奋了. 我的思想是对的, 细化逻辑是类人思考的一种重要方式. 在这里
    作者设计快速分词和 极快速小高峰过滤催化排序时候设计了一篇论证论文如下:
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